The present disclosure relates to an image processing method and an electronic apparatus with an image processing mechanism, and particularly relates to an image processing method and an electronic apparatus which can automatically process an image according to depth values.
Sometimes, a user may desire to alter an image after the image is captured. For example, the user wants to paste his image to an image for a place he has never been. Alternatively, the user may want to paste an image for a furniture to an image of a room to see if the furniture matches that room.
However, many altering steps are needed to complete this altering process. Firstly, the user must copy his image and paste his image to the image he wants. Secondly, the user must alter the location and the size for his image manually. However, the user may forget the real distance and the real size for the objects in the image he wants. Accordingly, the image after altered may be weird.
Take FIG. 1 for example, which is a schematic diagram illustrating a conventional image altering method, the user pastes the first object O1 (i.e. the user's image) in the first image I1 onto the second image I2 which comprises an image for a house (the second object O21) and an image for a tree (the second object O22), to generate an image I3. However, the first object O1 is large since the camera is near the people while shooting a photo, and the second objects O21 and O22 are small since the camera is far from the house and the tree while shooting a photo. Therefore, if the user does not alter the size of first object Ob1 after pasting the first object Ob1 onto the second image I2, the third image I3 will be weird. However, the user may not know what are the most suitable size and location for the first object O1 in the second image I2.